In the manufacture of many materials, crystallographic features, such as crystallographic orientation, grain size and grain morphology of the material, play an important role in determining the quality and characteristics of the resultant materials. For example, in a metal fabrication process, samples can be taken from the metal at a step in the metal fabrication process and examined, such as by using a microscope, to characterize the crystallography of the sample. Using statistical techniques, the overall quality of the process can be determined by comparing the samples' crystallography to a desired crystallography. However, such conventional techniques usually require destructive sampling of the manufactured metal, and are generally performed “off-line”, that is, they are performed separately from the fabrication process and the results of the sampling are generally not used to concurrently control an ongoing process. The information derived from the crystallography of the samples is applied to another fabrication batch.
In another example, some of the primary concerns in the manufacture of semiconductor devices are the mechanical and electrical properties of the metallization used to carry electrons within the semiconductor device. As the fabrication technology of semiconductors becomes more sophisticated, the physical properties of the materials used in semiconductor device, such as the complexity of preferred orientations of polycrystalline microstructures, becomes increasingly important. Crystallographic orientation, grain size and grain morphology play major roles in the reliability, quality assurance, electrical migration resistance, electrical properties, chemical-mechanical polishing (CMP) removal rates, and CMP endpoint detectability.
The crystallographic microstructure of material in a fabrication process can be examined with a variety of techniques including multiphase two-dimensional mapping of crystallographic and morphological data provides challenges to determine the crystallographic grain orientation, grain size and grain boundaries of a workpiece. There are many types of both optical and electron-based metrology tools available for this analysis, including scanning electron microscopes, focused ion beam microscopes, focused x-ray microscopes and focused optical microscopes including near-field scanning optical microscopes. The critical dimension scanning electron microscope (CD-SEM) utilizes algorithms based upon the intensity of line scan profiles of images to extract the apparent width of surface features. Another technique for nondestructively examining microelectronics devices is scanning probe microscopy (SPM) wherein a probe tip is used to study the surface topography or properties of the surface of a substrate. SPM tools include the atomic force microscope (AFM) and the stylus nanoprofilometer (SNP). Furthermore, scatterometers, such as ellipsometers, have been proposed for obtaining high speed two dimensional topographic information. Accordingly, there are numerous ways of obtaining this information, but each of the methods presents slightly different information and may not be suitable for providing process control in near real time manner concurrently with a fabrication process.
Grains within polycrystalline materials generally have orientations that vary from grain to grain. This variation, when considered over a bulk specimen area, can lead to the directional grouping of specific crystalline planes with respect to certain crystallographic axes. The “preferred orientation” of a workpiece refers to an average, or overall, orientation of the grains. The complexity of the preferred orientation of polycrystalline microstructures can be examined with a technique known as Orientation Imaging Microscopy, which analyzes collections of electron backscattering diffraction patterns. This technique combines the advantages of point orientation in Transmission Electron Microscopy (TEM) with morphological information over a large enough area to provide statistical relevance. However, this technique is prohibitively time consuming and does not lend itself to analysis of a metal process in a near real time environment to allow concurrent control of the process.
The foregoing meteorological techniques are typically conducted off-line, i.e., by taking partially fabricated structures in fabrication, including semiconductor devices, out of the fabrication sequence. It is believed that “inline,” analysis techniques (that is, a concurrent analysis step that can monitor and control a process while the process is continuing) that identify either grain size or preferred orientation of polycrystalline films do not currently exist in the art. For example, in the case of semiconductors, the devices are typically destructively measured offline by time consuming techniques of electron diffraction and x-ray diffraction. The disadvantage of these offline techniques is that they require constant monitoring on test structures and wafers, which results in a window between when problems occur and when problems are detected. While it is known to apply a neural network to fabrication systems to provide a degree of in-process control for an etch process (see, for example, U.S. Pat. No. 5,653,894 issued to Ibbotson, et al., and U.S. Pat. No. 5,737,496 issued to Frye, et al.), further improvements are desired.
Therefore an improved, inline method and system for monitoring and control of a fabrication process is needed.